Hard disk fault prediction method, device and equipment and computer readable storage medium

Abstract

The invention discloses a hard disk fault prediction method, device and equipment and a computer readable storage medium. When a hard disk fault prediction model for various hard disk models is established, a conversion relationship between each parameter of each hard disk model and a corresponding parameter of a reference hard disk model is firstly established, and then parameter detection valuesof the hard disks are converted according to the conversion relationship, so that the difference between different hard disk models is eliminated; a hard disk fault prediction model is trained by utilizing the converted parameter detection value and the running state of the hard disk; therefore, a hard disk fault prediction model suitable for various hard disk models is established; compared witha mode of independently training a hard disk fault prediction model for each type of hard disk, time and labor are saved; when the hard disk fault prediction model is used for hard disk fault prediction, since the association between the parameter of each hard disk model and the reference hard disk model is established, compared with the prediction model which only distinguishes different hard disk faults through models in the prior art, a more accurate prediction result can be obtained.

Description

technical field [0001] The invention relates to the technical field of hard disk monitoring, in particular to a hard disk failure prediction method, device, equipment and computer-readable storage medium. Background technique [0002] In large-scale data centers, the use of hard disks has reached the level of millions. The frequent occurrence of hard disk failures will lead to a decline in the stability and reliability of servers and even the entire IT infrastructure, which will ultimately have a negative impact on business service level SLAs. In recent years, industry and academia have carried out a lot of work related to hard disk failure prediction. In large-scale hard disk failure prediction, the most critical input data is hard disk parameter S.M.A.R.T (Self-Monitoring Analysis and Reporting Technology, self-monitoring, analysis and reporting technology) information. [0003] The distribution of S.M.A.R.T characteristics of hard disks produced by different manufacture...

AI Technical Summary

Problems solved by technology

For this reason, there are two common solutions. Either train the failure prediction model for each type of hard disk separately, and the modeling work is cumbersome due to the large number of hard disk models; or learn the hard disk model as a training feature, but the obtained hard disk The training accuracy of the failure model is not high

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